• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.45-54
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• 2012

Location-based services with GPS positioning technology as a key technology, but recognizing the current location through satellite communication is not possible in an indoor location-aware technology, low-power short-range communication is primarily made of the study. Especially, as Chirp Spread Spectrum(CSS) based location-aware approach for low-power physical layer IEEE802.15.4a is selected as a standard, Ranging distance estimation techniques and data transfer speed enhancements have been more developed. It is known that the distance measured by CSS ranging has quite a lot of noise as well as its bias. However, the noise problem can be adjusted by modeling the non-zero mean noise value by a scaling factor which corresponds to the change of magnitude of a measured distance vector. In this paper, we propose a localization system using the CSS signal to measure distance for a mobile node taken a measurement of the exact coordinates. By applying the extended kalman filter and least mean squares method, the localization system is faster, more stable. Finally, we evaluate the reliability and accuracy of the proposed algorithm's performance by the experiment for the realization of localization system.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.374-385
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• 2010

Wireless mesh networks can be deployed for various networks from home networking to last-mile broadband Internet access. Wireless mesh networks are composed of mesh routers and mesh clients. In these networks, static nodes form a multi-hop backbone of a large wireless access network that provides connectivity to end-users' mobile terminals. The network nodes cooperate with each other to relay data traffic to its destinations. In order to increase connectivity and better performance, researchers are getting interested in multi-channel and multi-interface wireless mesh networks. In these networks, non-overlapping multiple frequency channels are used simultaneously to increase the aggregate bandwidth available to end-users. Recently, researches have focused on finding suitable channel assignments for wireless network interfaces, equiped in a mesh node, together with efficient routing to improve overall system throughput in wireless mesh networks. This goal can be achieved by minimize channel interference. Less interference among using channels in a network guarantees more aggregated channel capacity and better connectivity of the networks. In this thesis, we propose interference aware channel assignment and routing algorithms for multi-channel multi-hop wireless mesh networks. We propose Channel Assignment and Routing algorithms using Traffic Profiles(CARTP) and Routing algorithms allowing detour routing(CARTP+2). Finally, we evaluate the performance of proposed algorithms in comparison to results from previous methods using ns-2 simulations. The simulation results show that our proposed algorithms can enhance the overall network performance in wireless mesh networks.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.73-86
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• 2019

After the 4th industrial revolution, the healthcare industry is striving to find new business models through new technologies. Among them, blockchain technology is one of the technologies that have great interest in the healthcare industry. Most providers of personal health record systems have difficulty in securing marketability due to various problems. Therefore, they try to integrate blockchain technology to develop new systems and gain marketability. However, blockchain has limitations in solving the problems of the personal health record system. In this study, we have designed a personalized health data management framework that enables information subjects to acquire full ownership rights of individual's health data, based on distributed ledger technology. For the framework design, we refer to the structure of R3 Corda. It was designed with a different network structure than the existing blockchain systems so that the node can be operated on the personal user's mobile device. This allows information subjects to directly store and manage their own data and share data with authorized network members. Through the proposed system, the information utilization of the healthcare industry can be improved and the public health promotion and medical technology development can be realized.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.131-139
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• 2022

In this paper, to verify the authenticity of UxNB that assists terrestrial base stations, the solutions for SI (System Information) security presented in 3GPP TR 33.809 are analyzed from the perspective of UxNB. According to the definition of 3GPP (Third Generation Partnership Project), UxNB is a base station mounted on a UAV (Unmanned Aerial Vehicle), is carried in the air by the UAV, and is a radio access node that provides a connection to the UE (User Equipment). Such solutions for SI security can be classified into hash based, MAC (Message Authentication Codes) based, and digital signature based, and a representative solution for each category is introduced one by one. From the perspective of verifying the authenticity of UxNB for each solution, we compare and analyze the solutions in terms of provisioning information and update, security information leakage of UxNB, and additionally required amount of computation and transmission. As a result of the analysis, the solution for verifying the authenticity of the UxNB should minimize the secret information to be stored in the UxNB, be stored in a secure place, and apply encryption when it is updated over the air. In addition, due to the properties of the low computing power of UxNB and the lack of power, it is necessary to minimize the amount of computation and transmission.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Radiation Oncology Journal
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• v.11 no.2
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• pp.267-275
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• 1993

Eighty five patients of oral cavity cancer, treated with radiation at the Department of Therapeutic Radiology, Korea Cancer Center Hospital, during the period from March 1985 to September 1990 were analyzed retrospectively. Among 85 patients, 37 patients were treated with radiation only and 48 patients were treated with radiation following surgery. And 70 patients received external irradiation only by $^{60}Co$ with or without electron, the others were 7 patients for external irradiation plus interstitial implantation and 8 patients for external irradiation plus oral cone electron therapy. Primary sites were mobile tongue for 40 patients, mouth floor for 17 patients, palate for 12 patients, gingiva including retromolar trigone for 10 patients, buccal mucosa for 5 patients, and lip for 1 patient. According to pathologic classification, squamous cell carcinoma was the most common (77 patients). According to AJC TNM stage, stage I + II were 28 patients and stage III+IV were 57 patients. Acturial overall survival rate at 3 years was $43.9\%,$ 3 year survival rates were $60.9\%$ for stage I + II, and $23.1\%$ for stage III+IV, respectively. As a prognostic factor, primary T stage was a significant factor (p<0.01). The others, age, location, lymph node metastasis, surgery, radiation dose, and cell differentiation were not statistically significant. Among those factors, radiation plus surgery was more effective than radiation only in T3+T4 or in any N stage although it was not statistically sufficient (p<0.1). From those results, it was conclusive that definitive radiotherapy was more effective than surgery especially In the view of pertainig of anatomical integrity and function in early stage, and radiation plus surgery was considered to be better therapeutic tool in advanced stage.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.